Self-similarity Analysis of Cartographic Lines and the Automated Line Generalization

Wang Qiao

美国《工程索引》（EI）核心期刊
美国《剑桥科学文摘》（CSA）收录期刊
荷兰斯高帕斯数据库（Scopus）收录期刊
英国INSPEC数据库（SA）收录期刊

Message Board

Respected readers, authors and reviewers, you can add comments to this page on any questions about the contribution, review, editing and publication of this journal. We will give you an answer as soon as possible. Thank you for your support!

Name
E-mail
Phone
Title
Content
Verification Code

PDF
Cite
Share

facebook

twitter

google

linkedin

Volume 20 Issue 2

Feb. 1995

Turn off MathJax

Article Contents

Article Navigation > Geomatics and Information Science of Wuhan University > 1995 > 20(2): 123-128

Wang Qiao. Self-similarity Analysis of Cartographic Lines and the Automated Line Generalization[J]. Geomatics and Information Science of Wuhan University, 1995, 20(2): 123-128.

Citation:

Wang Qiao. Self-similarity Analysis of Cartographic Lines and the Automated Line Generalization[J]. Geomatics and Information Science of Wuhan University, 1995, 20(2): 123-128.

Self-similarity Analysis of Cartographic Lines and the Automated Line Generalization

Wang Qiao

Dept. of Land Information and Cartographic Science, WTUSM, 39 Louyu Road, Wuhan, China, 430070

Received Date: 1994-08-31
Publish Date: 1995-02-05

Abstract

By discussing the self-similarity and fractal dimension of cartographic lines,the features of cartographic lines in shape are quantitated and extracted,and a new automatic generalization method for cartographic lines is proposed.This method has a good effect on maintaining the shape features,quantization and modelization of the proceducre of cartographic generalization,and provides a new solution to some problems difficult to solve with other methods in the automatic cartography.
- automatic cartography,
- self-similarity,
- fractal dimension
References
Proportional views

通讯作者: 陈斌, bchen63@163.com

1.
沈阳化工大学材料科学与工程学院沈阳 110142

Get Citation

PDF

XML

Article Metrics

Article views(728) PDF downloads(203) Cited by()

Proportional views